T cell mechanisms of immunotherapy response in pancreatic ductal adenocarcinoma
T cell mechanisms of immunotherapy response in pancreatic ductal adenocarcinoma
批准号:
10324557
负责人:
Emily Davis
金额:
$2.79万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-02-01 至 2022-06-15
关键词:
AddressAftercareAlgorithmsAllogenicAmino AcidsAntigensAntitumor ResponseAutomobile DrivingBase SequenceBenchmarkingBindingBiologicalBiological ProcessCancer BiologyCancer PatientCancer VaccinesCellsClassificationClinicalClinical TrialsClonal EvolutionCombination immunotherapyCombined VaccinesComplementComputer softwareComputing MethodologiesDataData SetDatabasesDisease regressionEntropyEventEvolutionFlow CytometryFutureGene ExpressionGene Expression ProfileGenetic TranscriptionGrantGranulocyte-Macrophage Colony-Stimulating FactorHeterogeneityHumanImmuneImmune checkpoint inhibitorImmune responseImmunologicsImmunomodulatorsImmunophenotypingImmunotherapeutic agentImmunotherapyIndividualInfiltrationMalignant NeoplasmsMalignant neoplasm of pancreasMeasurementMethodsModalityModelingMusMutationNormal CellPancreatic Ductal AdenocarcinomaPathway interactionsPatientsPerformancePlantsPopulationProcessPropertyProteinsRNAResearchResistanceResolutionScientistSpecificityT cell clonalityT cell receptor repertoire sequencingT-Cell Antigen Receptor SpecificityT-Cell ReceptorT-LymphocyteTestingTherapeuticTreesTumor AntigensTumor ImmunityTumor-infiltrating immune cellsVaccinesWorkanti-tumor immune responsebasecancer typecareercombinatorialeffector T cellexhaustionhuman dataimmune activationimmune functionimmunogenicimprovedinnovationinsightmachine learning classifiermelanomamouse modelmutantneoantigen vaccineneoantigensopen sourcepancreatic ductal adenocarcinoma modelpersonalized immunotherapypreventresponsesingle-cell RNA sequencingskillssuccesstranscriptomicstreatment armtreatment responsetumor
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英文摘要
Project Summary
Immune checkpoint inhibitors (ICIs) provide durable clinical responses in about 20% of cancer patients, but have
been largely ineffective for non-immunogenic cancers that lack intratumoral T cells. Most tumors have somatic mu-
tations that encode for mutant proteins that are tumor-specific and not expressed on normal cells (termed neoanti-
gens). Cancers, such as melanoma, with the highest mutational burdens are more likely to respond to single agent
ICIs. However, most cancers, including pancreatic ductal adenocarcinoma (PDAC), have lower mutational loads,
resulting in fewer T cells infiltrating the tumor. Studies have previously demonstrated that an allogeneic GM-CSF-
based vaccine enhances T cell infiltration into human pancreatic cancer. Recent work with Panc02 cells, which
express around 60 neoantigens similar to human PDAC, showed that PancVAX, a neoantigen-targeted vaccine,
when paired with immune modulators cleared tumors in Panc02-bearing mice. This data suggests that cancer
vaccines targeting tumor neoantigens induce neoepitope-specific T cells, which can be further activated by ICIs,
leading to tumor rejection. Currently the impact of such treatment on T cell expression states and the underly-
ing mechanism of therapeutic response remains poorly defined. Comprehensive characterization of responding T
cells will be critical in understanding mechanisms of response and providing rationale for combinatorial therapy. In
this proposal we will test the hypothesis that when used alongside neoantigen-targeted vaccines, individual ICIs
have distinct as well as synergistic modes of action and that different treatment combinations result in distinct
changes in the T cell repertoire related to immunotherapy response. To address this hypothesis, I propose two
specific aims. Aim 1: To characterize the transcriptional changes in T cells during immunotherapy treatment. I will
first investigate the effect of PancVAX, with and without addition of ICIs, on gene expression at a single-cell level
in the Panc02 mouse model. Then I will determine biological processes driving differences in anti-tumor response
between treatment arms. I will experimenally validate these differences using flow cytometry. Aim 2: To develop
trajectory building methods depicting the clonal evolution of T cells. We will apply this method to T cell receptor
sequencing data from human clinical trials of PDAC treated with vaccine and ICI to identify key changes within the
T cell repertoire associated with tumor regression or resistance. Successful completion of these aims will inform
future combination immunotherapy approaches in PDAC patients and provide new open-source computational
software to characterize T cell populations that can be applied to diverse cancer types. The skills I will acquire
as I complete this research will prepare me for a career as an interdisciplinary scientist, characterizing the tumor
immune landscape to inform precision immunotherapy.
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